Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

[Objective] The objective of this work was to analyze the use of organic insecticides from extracts of different plants to control the impact produced by the caterpillar pest Spodoptera spp. on the watermelon (Citrullus lanatus) crop in the province of Los Ríos, Ecuador. [Methodology]  A randomized complete block design (RCBD) was used, consisting of five treatments with four replicates, with different extracts and a control. Treatment T1 consisted of Capsicum sativum chili bell pepper extract plus common soap; treatment T2 consisted of Allium sativum garlic extract with liquid paraffin vegetable oil plus common soap; treatment T3 consisted of Urtica dioica nettle extract; treatment T4 consisted of Ruta graveolens rue extract, and treatment T5 was defined as a control. Differences between results of treatments were compared using Tukey’s test. Results were considered to be statistically significant when p ≤ 0.05. [Results] The T3 treatment was most effective, producing the lowest percentage of pest incidence (an average of 25%), and the lowest percentage of fruit damage (an average of 10%). It was followed by T1 (32.50% pest incidence) and T2 (35.00% pest incidence). The T5 control produced negative results, with 50% pest incidence and 37.50% fruit damage. [Conclusions] The study demonstrated that nettle extract, used as a botanical extract for the potential control of Spodoptera spp. in the watermelon crop produced the lowest incidence of pests (25%), demonstrating the usefulness of botanical extracts in sustainable horticultural production.

The objective was to develop an automated algorithm for the estimation of a protein (Ki-67) index based on cell nuclei area ratio of gastric epithelial tissue cells; for this purpose, digital histopathology images were used. An expert manually annotated each region of interest of the images. A proportion of Ki-67 positive and negative cells within that region was used to obtain the color distribution of the corresponding pixels. The histogram of each color distribution was modeled as a Gaussian and, later, thresholded for segmentation and classification. Finally, the Ki-67 index was estimated as the ratio between the segmented positive area of the nuclei divided by the total area of the positive and negative nuclei. The automated method has a strong correlation of 0.725 and a root mean square error of 0.293 when compared to the manual method, which gives certainty that the automated method can be used to analyze the proliferation rate. Furthermore, compared to manual classification, the presented method automatically classifies every image in the same Ki-67 category: low, intermediate, and high. Despite the small sample size, the utility of the presented method was demonstrated. However, the low number of scored images did not allow for thoroughly sampling the ranges of pixel values and intensities observed by pathologists, which will be addressed in future work.

[Objective] The transformation from RGB to Munsell color space is a relevant issue for different tasks, such as the identification of soil taxonomy, organic materials, rock materials, skin types, among others. This research aims to develop alternatives based on feedforward networks and the convolutional neural networks to predict the hue, value, and chroma in the Munsell soil-color charts (MSCCs) from RGB images. [Methodology] We used images of Munsell soil-color charts from 2000 and 2009 versions taken from Millota et al. (2018) to train and test the models. A division of 2856 images in 10% for testing, 20% for validation, and 70% for training was used to build the models. [Results] The best approach was the convolutional neural networks for classification with 93% of total accuracy of hue, value, and chroma combination; it comprises three CNN, one for the hue prediction, another for value prediction, and the last one for chroma prediction. However, the three best models show closeness between the prediction and real values according to the CIEDE2000 distance. The cases classified incorrectly with this approach had a CIEDE2000 average of 0.27 and a standard deviation of 1.06. [Conclusions] The models demonstrated better color recognition in uncontrolled environments than the Transformation of Centore, which is the classical method to transform from RGB to HVC. The results were promising, but the model should be tested with real images at different applications, such as soil real images, to classify the soil color.

Problem posing, as a genuinely mathematical activity, provides an inexhaustible source of alternatives in a classroom. Many authors, as well as institutions such as the National Council of Teachers of Mathematics, highlight the importance of this mathematical practice. With this case study, we intend to demonstrate the characteristics of the type of knowledge used by a teacher when implementing this type of session in 4-year-olds, with an emphasis on the knowledge used for planning and putting the session into practice. We used fragments of the session’s recording, as well as a subsequent interview with the informant, in order to corroborate the information identified during the data analysis. The specific mathematical nature of this activity leads us to use the MTSK model (Mathematics Teachers’ Specialized Knowledge) as a reference to analyze the specialized knowledge that a pre-school teacher uses during a classroom practice. This practice is comprised of two tasks, both created and designed by the informant teacher. Results show aspects of knowledge related to MK (Mathematical Knowledge), but, above all, PCK (Pedagogical Content Knowledge) predominance, evidencing the importance of this type of knowledge in early childhood education to implement a problem posing session.

This work aims to measure the impact of approximate computing on a case study of traffic dynamics metering on a System-on-Chip edge computing device. Firstly, the study proposes a baseline implementation of the metering system in C++. To analyze the application in detail, study profiled the baseline using a built-in instrumented profiler, presenting the overall performance of each of its parts. During the hotspot analysis, some parts had optimization opportunities exploitable by multi-threading and approximate computing techniques, particularly frame skipping, which is inspired by the loop perforation approximate technique. The first optimization employed was multi-threading, which led to a 1.32x speedup on the application without introducing errors in the metrics. Then, the meter was optimized by using frame skipping. This work demonstrated that adaptatively modifying the number of frames skipped improved the error in the final metrics compared to keeping it fixed. In terms of performance, the frame skipping brought the overall speed up to 1.76x. Approximate computing, in particular, frame skipping, managed to contribute up to 25% of the overall speedup, managing to accelerate the meter from 8.7 frames per second to 15 fps in the most critical case in exchange for some numerical error on the final metrics.

This article summarized the knowledge obtained from exercises with patients using computer-assisted rehabilitation. Working with a wide base of healthy individuals and patients with various problems yielded the results to summarize. This work utilized several rehabilitation devices using computer games and uncovered positive and negative aspects of contemporary rehabilitation procedures. we conclude in this research computer-assisted rehabilitation is the future of modern rehabilitation, so it is necessary to know all factors affecting patients’ health.

 [Objective] The purpose of the present study was to analyze the relationship between students’ mathematical self-efficacy and performance in the national high school graduation mathematics test, taking into account other relevant psychosocial predictors and the moderating effects of sex and educational center. [Methodology] The design of the study was observational and cross-sectional, with the participation of 487 eleventh-grade students from public secondary schools in the Greater Metropolitan Area of Costa Rica. Several instruments were applied for measuring hostile and benevolent sexism, perceptions of gender equality in mathematical abilities, mathematical self-efficacy and reasoning abilities. [Results] The results of the multilevel Bayesian random effects analysis confirmed that scores were higher for men than for women in measurements of self-efficacy, where the sex of the student body was a moderator in the relationship of mathematical self-efficacy and test scores. In addition, it was found that, depending on the sex of subjects, the association between self-efficacy and performance was also moderated by the educational center. [Conclusions] Among the conclusions, it is especially noteworthy that if the moderating effect of the educational center between self-efficacy and performance differs by sex, this implies that actions aimed at promoting self-efficacy will not have the same result in men and women, showing the need to develop differentiated interventions.

[Objective] This investigation seeks to determine the difference in bone level around implants adjacent to teeth and implants. [Methodology] This cross-sectional study included 17 patients with a total of 51 stable implants with a functional loading of at least 6 months. These implants were located next to natural teeth, other implants, or both. All implants and adjacent teeth were clinically examined, and periodontal and peri-implant parameters were recorded. A radiographic analysis was carried out to measure the bone level around implants in relation to the implant platform. Data were analyzed to detect differences between bone levels on the side of an implant next to a tooth compared to those on the side of an implant next to another implant. Statistical differences were considered significant when p≤0.05. [Results] The distance from the crestal bone on the coronal side of the implant platform to adjacent teeth or implants was approximately 1 mm. The bone level in zones adjacent to other implants was more apically located (2.9 ± 1.4 mm) than was the case for bone levels on sides adjacent to natural teeth (1.3 ± 0.07 mm) and the difference in these distances was statistically significant (p<0.05). Bivariate analysis showed that the bone level around implants was more likely to be coronal in relation to the implant platform on the side adjacent to a tooth than on the side adjacent to another implant (p=0.04). [Conclusions] The results indicate that the bone level of implants adjacent to natural teeth is maintained more coronal as compared to implants adjacent to other implants. This suggests a greater stability of implants when they are located near remaining natural teeth.

[Objetivo] El objetivo de esta investigación fue analizar los tipos de tránsitos en un ciclo de modelación que estudiantes chilenos realizaron en una tarea interdisciplinar de modelación matemática. [Metodología] Para responder al objetivo de investigación planteado, la metodología utilizada fue de tipo cualitativa, y consistió en un estudio de caso en donde se implementó una tarea de modelación matemática, basada en el ciclo de modelación de Blum-Borromeo, a 5 estudiantes de último año de secundaria de un colegio privado de Chile. El diseño de la tarea incorporó componentes presentes en los programas de estudio de Historia, Geografía y Ciencias Sociales, Matemáticas y las cuatro competencias propuestas por OCDE en términos de Educación Financiera. [Resultados] Como resultado de la investigación, se tuvo que los estudiantes realizaron 3 diferentes tipos de tránsito en el ciclo de modelación, que han sido relacionados con su nivel de alfabetización financiera: el primer tránsito, basado en ajustes en el modelo real; el segundo tránsito, basado en ajustes desde los resultados reales, y el tercer tránsito, basado en ajustes en el modelo real, a partir de los resultados reales. Con base en estos resultados, se llevó a cabo una discusión acerca de los niveles de alfabetización financiera de los estudiantes. [Conclusiones] Se concluyó que tareas de modelación interdisciplinares como las presentadas en esta investigación son entornos adecuados para desarrollar los niveles de alfabetización financiera de los estudiantes.

To promote mathematical learning, teachers must be able to analyze, interpret and assess students’ mathematical activity, making decisions about their understanding of, and difficulties in, solving mathematical tasks. This cognitive analysis skill enables teachers to understand mathematical learning processes and to establish different ways of institutionalizing the mathematical knowledge involved. [Objective] This work is intended to present the results of an assessment of preservice Primary Education teachers’ knowledge and abilities to interpret students’ responses to probability comparison tasks, identify incorrect strategies and recognize proportional reasoning in mathematical activity. Furthermore, the strategies proposed by preservice teachers to help students overcome the difficulties that led them to obtain inadequate solutions are analyzed. [Methodology] Descriptive and qualitative research was carried out with the collaboration of 116 preservice Primary Education teachers from the University of Almería (Spain). The investigation was carried out once the process of training in the mathematical contents of Statistics and Probability had been completed. [Results] One of the most important results obtained is a didactic-mathematical knowledge of the type of proportional and probabilistic reasoning that impedes preservice teachers in their interpretation and decision-making about student responses. [Conclusions] These results highlight the need to implement educational solutions to adequately resolve these common situations in schools.